Brief:
- Cardiovascular disease is a significant health concern worldwide despite having many genomics developments providing valuable new candidates for better biomarkers and novel therapeutic targets. This blog focuses on recent trends in this field of genomic biomarkers.
- DNA microarrays, linkage analysis, genome-wide association studies, and other strategies give significant knowledge about the heart’s metabolic diseases. Consisting of many benefits from these approaches, but one must remain conscious of the importance of phenotyping.
- The integration of new technologies promises the discovery and validation of better biomarkers of the presence of cardio disease, its progression, and the response to treatment in this blog.
Introduction:
Recent advancements in the incidence of the cardio disease continue upward globally, yielding a significant impact on morbidity and mortality in Clinical research organization. The number of patients suffering from CVD (Cardiovascular diseases) mounts, with an ageing demographic. The economic and burdens of these diseases will continue to grow, with tremendous consequences in healthcare systems. The search for better biomarkers of the disease’s presence and progression response to treatment has become a matter of urgency. Luckily, technological advances have facilitated high-throughput assessment and mining of the human genome, proteome, and metabolome. In this context, molecular signatures will be increasingly useful in predicting, diagnosing, and managing heart disease. The discovery and development of biomarkers have benefited from the emergence of high-performance genomic and genetic approaches such as DNA microarrays and single nucleotide polymorphism chips, respectively, in Clinical trial Monitoring Services. The ability to screen large populations for gene expression levels and genetic linkage has shed light on the complex interplay of genetic factors involved in CVD. Molecular signatures identify both in the clinical management of disease and in elucidating the mechanisms involved and provide novel therapeutics for Clinical Biostatistics services.
Analyzing the Gene expression
Rise of technologies such as DNA microarrays and analyses of gene expression in various cardiovascular diseases are significant to the pharmaceutical regulatory consulting services. The amount of transcribed genes and the related mRNAs are detectable by the microarrays to discover correlations of diseases, clinical outcome, disease progression, and therapeutic responses. Microarray analysis comparing the expression of genes in non-failing hearts and failing hearts. In a study, 288 genes identifying as differentially expressed between groups with non-failing and failing hearts. Although none of the genes is currently useful for clinical purposes, these biomarkers can still provide therapeutic benefits into the metabolic dysregulation underlying the disease conditions with the healthcare data analytics services. As described, many of the genes up-regulated in failing hearts, relative to those in the non-failing hearts, connected with fatty acid metabolism, whereas those down-regulated relates to glucose metabolism using clinical study design. It has triggered an investigation into the use of drugs to shift the lipid and glucose metabolic defines in myocardial cells, as a potential treatment for heart failures. Gene expression studies have also highlighted the importance of regulation of lipid metabolism in atherosclerosis. Using mouse models, identified numerous genes involved in lipid metabolism contain expression differentially in cardiovascular diseases such as ischemic and non-ischemic diseases. A single biomarker can provide sensitively and specifically as the therapeutic or diagnostic biomarker for the disease. Biomarkers of the future expect to be multi-marker panels characteristic of the disease processes’ complexity underlying pathophysiology. Only a small quantity of sporadic atherosclerosis results from single-gene defects in lipid metabolic pathways.
Genome-wide association studies
Beyond microarray-based expression studies, genome-wide association studies provide a practical approach to discovering genetic biomarkers. Gene variants, on chromosome 9 and chromosome 4 have connects to increased risk for CVD. The applied genome-wide association scanning found a 58 kb interval on chromosome 9p21 that was consistently associated with coronary heart disease in six independent cohorts, from more than four white populations. Another similar finding found an association between a similar region on chromosome 9p21 and coronary artery disease. In the study, two sequence variants on chromosome 4q25 present to be strongly connected with a clinical trial fibrillation among the three populations of European descent. In some instances, the risk locus identified via genome-wide association studies contains genes that have yet to be annotated and characterized. It may also be unclear what these genetic variants induce cellular and molecular differences. Indeed, the newly identified susceptibility loci or SNPs require studies to analyze their involvement in CVD pathogenesis and potential therapeutic analysis for testing. Each SNP may likely have a modest influence on the concentrations or function of translated protein products. In contrast, a specific set of SNPs can significantly impact the pathobiology of a particular CVD. Like genes identified in microarray studies, SNPs contain valuable information for CVD mechanisms and potential new therapeutics.
Linkage analysis
Linkage analysis is another approach to finding genetic biomarkers of heart diseases. It permits the identification of infection with DNA markers by examining the patterns of heredity and disease phenotypes among the family members. The linkage analysis looked at families with early-onset coronary artery disease and demonstrated an association between GATQA2, a transcription factor, and susceptibility for coronary artery disease. Recent studies in Coronary Artery Diseases investigations also revealed novel gene candidates, such as LSAMP, a tumour suppressor gene, and KALRN, a gene involved in the Rho GTPase signalling pathway, to be associated with coronary artery disease for therapeutics clinical research.
Wrapping up:
The critical factor to consider when comparing different genetic biomarkers studies is the selection of the patient cohort. It depends on the heterogeneity of the population’s size; the genetic biomarkers detected may be significantly different. Ultimately, the genetic biomarkers obtained using various technologies will be complementation. Future systems in biology studies shed light in this regard and provide a complete picture of each CVD’s genetic mechanisms. Genetic biomarkers may also help uncover, the human genome contains more than 22 000 genes. These current trends of genetic biomarkers are listed in this blog.
References:
- McManus, Bruce. “Trends in genomic biomarkers.” Heart Metab43 (2009): 19-21.
- Radpour, R., Barekati, Z., Kohler, C., Holzgreve, W., & Zhong, X. Y. (2009). New trends in molecular biomarker discovery for breast cancer. Genetic Testing and Molecular Biomarkers, 13(5), 565-571.
- Srinivas, P. R., Kramer, B. S., & Srivastava, S. (2001). Trends in biomarker research for cancer detection. The lancet oncology, 2(11), 698-704.
